The paper presents a repeatable method for confirming which specific URL filtering product is used for censorship: create test domains under researcher control, submit a subset to the vendor's public URL categorization interface, then retest within 3–5 days to observe whether submitted domains become blocked. This technique confirmed McAfee SmartFilter in UAE (Etisalat, AS 5384) and Saudi Arabia (Bayanat Al-Oula AS 48237, Nournet AS 29684), and Netsweeper in Qatar (Ooredoo AS 42298), UAE (Du AS 15802), and Yemen (YemenNet AS 12486).

All confirmed URL filtering deployments—McAfee SmartFilter in UAE and Netsweeper in Yemen, UAE, and Qatar—block content across at minimum six of seven tested human-rights-sensitive categories: media freedom, human rights, political reform, LGBT, religious criticism, and minority groups/religions. Netsweeper in both Qatar (Ooredoo) and UAE (Du) blocks all seven categories. This content is protected under Article 19 of the Universal Declaration of Human Rights.

§5, Table 4 policy

In YemenNet (AS 12486), URL filtering was observed to be intermittently offline: proxy URLs accessible in one test run were blocked in others and vice versa. A prior ONI measurement found a Yemeni ISP running Websense whose filtering ceased entirely when concurrent user count exceeded the product's license capacity. This inconsistency required larger URL test sets and repeated measurement runs to establish blocking with high confidence.

§4.4 evaluation

In every ISP where URL filtering was empirically confirmed, the 'proxy anonymizer' category was actively blocked. Netsweeper blocked 6/6 submitted proxy domains in YemenNet (AS 12486), 5/6 in Du UAE (AS 15802), and 6/6 in Ooredoo Qatar (AS 42298); McAfee SmartFilter blocked 5/5 anonymizer-category submissions in Etisalat UAE (AS 5384). Blue Coat in UAE and Qatar did not confirm—Etisalat appears to use SmartFilter for URL filtering atop a Blue Coat proxy appliance for traffic management.

§4.3–4.5, Table 3 detection

URL filtering appliances are frequently misconfigured to be externally visible on the global Internet, enabling passive identification via Shodan keyword searches on product-specific HTTP headers and management console paths (e.g., 'cfru=' for Blue Coat, '8080/webadmin/' for Netsweeper). This technique discovered previously unknown installations in Finland, Sweden, Philippines, Thailand, Taiwan, Argentina, and Chile, as well as large U.S. ISPs including AT&T, Verizon, Bell South, Comcast, and Sprint.

§3, Figure 1 evaluation

The paper proposes a black-box methodology for detecting censorship bias in LLMs by comparing responses to identical prompts in Simplified vs. Traditional Chinese — scripts for the same spoken language — controlling for translation quality while exploiting that Simplified Chinese training data is disproportionately sourced from mainland China's censored internet. Each prompt is repeated ten times and scored for similarity to censored text using an XLM-RoBERTa classifier fine-tuned on Baidu Baike (censored) vs. Chinese Wikipedia (uncensored) with scores from 0 to 1.

2024-ahmed-extended §2 / §2.4 keyword-filteringml-classifiermeasurement-platform

The paper proposes detecting translation censorship by back-translating the Chinese text to English via Google Translate, embedding each paragraph with distiluse-base-multilingual-cased-v1, and solving a linear-sum-assignment bipartite matching weighted by negated cosine similarity. Paragraphs below a similarity threshold are flagged as cut; matched paragraphs are recursively compared at sentence level to detect alterations.

2023-streisand-where §2 Methodology keyword-filteringmeasurement-platform

Hong Kong Twitter users are 33% more likely than a random control sample to have protected their accounts, and over 247% more likely to have deleted past Tweets, after enactment of the June 2020 national security law (NSL). These differences are statistically significant at p ≤ 1.74e-48 for all account-protection and Tweet-deletion metrics.

2023-wang-self-censorship §4.1 / Table 2 keyword-filteringmeasurement-platform

Hong Kong Twitter discussion of COVID-19 continued declining after mid-2020 and did not resurge during Hong Kong's large March 2022 COVID wave, unlike the control group whose COVID discussion tracked local transmission rates. The authors interpret this anomalous pattern as a generalized chilling effect: NSL legal risk suppressed even politically ambiguous health discussion that mainland China had censored but that may not clearly fall under the NSL.

2023-wang-self-censorship §4.2 / Figure 2c keyword-filteringmeasurement-platform

Of inaccessible Tweets from 2019, those containing NSL-sensitive political keywords are disproportionately deleted or protected by both Hong Kong users (36.38% inaccessibility) and Taipei users (34.89%), compared to New York City (29.45%) and Tokyo (30.80%). This suggests that NSL legal exposure — which extends extraterritorially under Article 38 — may be chilling speech even among users outside Hong Kong who transit or have ties to mainland China.

2023-wang-self-censorship §4.1 / Table 3 keyword-filteringmeasurement-platform

While Hong Kong users sharply reduced discussion of NSL-sensitive political topics after July 2020, their rate of Tweeting about non-sensitive topics (travel, food, art, media) remained stable and mirrored control-group trends. This targeted suppression — rather than a general withdrawal from Twitter — confirms the NSL produced specific self-censorship of covered speech rather than platform abandonment.

2023-wang-self-censorship §4.2 / Figure 2b keyword-filteringmeasurement-platform